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torch dynamic profiling

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This commit is contained in:
Vladimir Mandic
2024-05-16 18:40:18 -04:00
parent d63f35e298
commit 554e5c8224
19 changed files with 45 additions and 29 deletions
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modules/processing_diffusers.py
+3 -3
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@@ -169,7 +169,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
p.ops.append('upscale')
if shared.opts.save and not p.do_not_save_samples and shared.opts.save_images_before_highres_fix and hasattr(shared.sd_model, 'vae'):
save_intermediate(p, latents=output.images, suffix="-before-hires")
shared.state.job = 'upscale'
shared.state.job = 'Upscale'
output.images = resize_hires(p, latents=output.images)
sd_hijack_hypertile.hypertile_set(p, hr=True)
@@ -211,7 +211,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
desc='Hires',
)
update_sampler(p, shared.sd_model, second_pass=True)
shared.state.job = 'hires'
shared.state.job = 'HiRes'
shared.state.sampling_steps = hires_args.get('num_inference_steps', None) or p.steps
try:
sd_models_compile.check_deepcache(enable=True)
@@ -230,7 +230,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
# optional refiner pass or decode
if is_refiner_enabled():
prev_job = shared.state.job
shared.state.job = 'refine'
shared.state.job = 'Refine'
shared.state.job_count +=1
if shared.opts.save and not p.do_not_save_samples and shared.opts.save_images_before_refiner and hasattr(shared.sd_model, 'vae'):
save_intermediate(p, latents=output.images, suffix="-before-refiner")